Learn Business Analytics in Six Steps Using SAS and R: A Practical, Step-by-Step Guide to Learning Business Analytics
- Length: 219 pages
- Edition: 1st ed.
- Language: English
- Publisher: Apress
- Publication Date: 2017-01-17
- ISBN-10: 1484210026
- ISBN-13: 9781484210024
- Sales Rank: #1175837 (See Top 100 Books)
Apply analytics to business problems using two very popular software tools, SAS and R. No matter your industry, this book will provide you with the knowledge and insights you and your business partners need to make better decisions faster.
Learn Business Analytics in Six Steps Using SAS and R teaches you how to solve problems and execute projects through the “DCOVA and I” (Define, Collect, Organize, Visualize, Analyze, and Insights) process. You no longer need to choose between the two most popular software tools. This book puts the best of both worlds―SAS and R―at your fingertips to solve a myriad of problems, whether relating to data science, finance, web usage, product development, or any other business discipline.
What You’ll Learn
- Use the DCOVA and I process: Define, Collect, Organize, Visualize, Analyze and Insights.
- Harness both SAS and R, the star analytics technologies in the industry
- Use various tools to solve significant business challenges
- Understand how the tools relate to business analytics
- See seven case studies for hands-on practice
Who This Book Is For
This book is for all IT professionals, especially data analysts, as well as anyone who
- Likes to solve business problems and is good with logical thinking and numbers
- Wants to enter the analytics world and is looking for a structured book to reach that goal
- Is currently working on SAS , R, or any other analytics software and strives to use its full power
Table of Contents
Chapter 1: The Process of Analytics
Chapter 2: Accessing SAS and R
Chapter 3: Data Manipulation Using SAS and R
Chapter 4: Discover Basic Information About Data Using SAS and R
Chapter 5: Visualization
Chapter 6: Probability Using SAS and R
Chapter 7: Samples and Sampling Distributions Using SAS and R
Chapter 8: Confidence Intervals and Sanctity of Analysis Using SAS and R
Chapter 9: Insight Generation